Tensor Deblurring and Denoising Using Total Variation

11/06/2021
by   Fatoumata Sanogo, et al.
0

We consider denoising and deblurring problems for tensors. While images can be discretized as matrices, the analogous procedure for color images or videos leads to a tensor formulation. We extend the classical ROF functional for variational denoising and deblurring to the tensor case by employing multi-dimensional total variation regularization. Furthermore, the resulting minimization problem is calculated by the FISTA method generalized to the tensor case. We provide some numerical experiments by applying the scheme to the denoising, the deblurring, and the recoloring of color images as well as to the deblurring of videos.

READ FULL TEXT

page 11

page 12

page 16

page 17

page 18

research
06/18/2023

Weighted structure tensor total variation for image denoising

Based on the variational framework of the image denoising problem, we in...
research
08/04/2018

Application of Bounded Total Variation Denoising in Urban Traffic Analysis

While it is believed that denoising is not always necessary in many big ...
research
01/26/2021

Tensor denoising with trend filtering

We extend the notion of trend filtering to tensors by considering the k^...
research
12/22/2017

Denoising of image gradients and total generalized variation denoising

We revisit total variation denoising and study an augmented model where ...
research
01/16/2020

Adaptive Direction-Guided Structure Tensor Total Variation

Direction-guided structure tensor total variation (DSTV) is a recently p...
research
07/28/2023

Uncertainty Quantification for Scale-Space Blob Detection

We consider the problem of blob detection for uncertain images, such as ...
research
02/06/2018

A Log-Euclidean and Total Variation based Variational Framework for Computational Sonography

We propose a spatial compounding technique and variational framework to ...

Please sign up or login with your details

Forgot password? Click here to reset